Is AI Higher Ed's Invisible COVID?

In March 2020, I was quarantined in a spare bedroom, sick and foggy with an illness that I'd never experienced before but would shake up our world, while sitting through a six-hour emergency conference call. COVID lockdowns were starting, and we had gathered the institution's cabinet and leadership team in a hastily created Zoom to lay out our path to survival.

Over the prior two days, my colleague, the brilliant Megan Broadwin, had cranked out 53 different Excel models that tested every scenario: enrollment projections, tuition refunds, student step-outs, the costs of moving online, even assumptions for various levels of marketing cuts, salary freezes, rent concessions, and debt relief.

Meanwhile, IT was scrambling to harden the network for nonstop Zoom traffic, academic teams were rushing to move classes online, and student services was, in real time, creating a new playbook. Decisions had to be made, and action had to be taken. Higher ed needed to pivot overnight, in direct contradiction to the slow committees and long debates that usually define it.

The question is: are we doing the same with AI? And should we be?

"The hardest thing to see is what is in front of your eyes." (Goethe)

COVID vs. AI: Different Signals, Same Scale of Disruption

COVID was visible and immediate. Students were questioning whether to enroll, and those already on campus were considering stepping out or taking time off. Refund requests began to appear. All of it created deep uncertainty about revenue, and institutions responded overnight.

I would contend that AI is quieter but no less disruptive.

Students aren't locked out of campus. They're finding new ways around traditional learning entirely. They use AI to finish assignments faster, get tutoring on demand, and explore alternative learning models. Employers are questioning whether a degree is still the best signal of readiness. New providers are emerging with AI-driven, stackable credentials at a fraction of the cost.

The risk for institutions isn't just academic integrity. It's structural:

Revenue models face pressure as students choose faster, cheaper and career-aligned AI-powered alternatives.

Cost structures remain fixed while demand shifts, leaving campuses financially exposed.

Decision-making processes remain slow and committee-driven, while new AI-powered competitors can launch and iterate rapidly without needing faculty senate approval or accreditation reviews.

COVID forced a tactical response. IT secured networks, faculty shifted courses online, finance modeled revenue shocks. Leaders acted quickly to keep the lights on.

AI feels different. Because it presents as a strategic question (curriculum design, credentialing, the future of teaching and learning), leaders may assume there's time to debate, study, and pilot. But that assumption may be the most dangerous part. What appears to be a gradual, manageable transition may actually be a rapid market shift disguised as academic evolution.

The Signals Are Already Here And Accelerating

AI may present differently than COVID, but it's no less a risk to the institution. And it's accelerating faster outside higher education than within it:

Students are experiencing AI-powered learning everywhere except campus. They use AI tutors for instant help, AI writing tools for rapid iteration, and AI-powered platforms that adapt to their learning pace in real time. Then they walk into classrooms that now feels a world away.

Agile competitors are offering higher ROI alternatives. While institutions spend months debating AI policies, new providers are developing AI-powered programs that seek to deliver job-ready skills in weeks, not years - available at a fraction of the investment of time and money.

The gap between campus and the real world is widening daily. While institutions debate, students are already fluent in AI tools and paradigms that will define their careers.

Students may increasingly see traditional education as backwards-looking. Why choose an institution that prohibits or restricts the tools that are transforming every industry? Why pay premium prices for a learning experience that feels artificially constrained compared to what's available for free online?

These aren't early signals anymore. They're market movements. The question isn't whether this will disrupt higher ed, but how quickly institutions will lose market share to more agile competitors.

The Leadership Test

With COVID, disruption was concrete and undeniable. Students weren't on campus, so leaders acted.

AI's disruption is subtler, but potentially more fundamental. If higher ed waits until the signs are as obvious as empty dorms, the opportunity to lead the change rather than react to it will already be gone.

We treated COVID like the existential threat that it was, mobilizing every resource and making decisions in days that would normally take months.

The question now is: are we treating AI the same way? And if not, should we be?

Geoff Baird

Dillon, Co